Understand Your Data. Then Improve It.
True North Circle does not view data quality as simply a coding or database problem. Healthcare data begins much earlier — with care, documentation and thousands of processes performed throughout the organization.
Data quality is a chain.
Healthcare organizations create and transform information hundreds of times before it becomes the data used for reporting, funding, research and decision-making. A quality problem visible at the end of that chain may have started much earlier.
True North Circle looks across the entire information lifecycle to identify where quality is being lost, why it is happening and what can be done about it.
A missed detail becomes a documentation issue. A documentation issue becomes a data issue.
A coding or workflow issue can affect reporting. That can ultimately affect organizational decision-making, resource allocation, funding, performance measurement, quality indicators, government reporting, research, policy — and patient care.
Data Quality & Process Assessment
Also known as the True North Data Quality Assessment. Depending on the organization, True North Circle may examine any part of the information lifecycle — the point is that we can follow a data-quality issue wherever the evidence leads. Not every engagement covers every area below.
Potential areas examined
- Clinical documentation
- Information capture at point of care
- Documentation completeness
- Physician documentation workflows
- Nursing and allied health documentation
- Coding and abstraction processes
- HIM workflows
- Data validation and quality control
- EHR workflows
- Interfaces between systems
- Manual processes and workarounds
- Roles and responsibilities
- Policies and procedures
- Staff capacity
- Education and knowledge gaps
- Reporting processes
- Data governance
- Data flows between departments
- Downstream data use
- Performance indicators
- Submission processes
- Existing technology and tools
The right solution starts with the right diagnosis.
A documentation problem requires a different response from a staffing issue, a workflow problem or a technology limitation. True North Circle identifies the cause first and recommends the intervention second.
Process Improvement
Redesign workflows and processes that create, transform or use healthcare information.
Documentation Improvement
Identify gaps in information capture and improve the processes that allow clinicians and other healthcare professionals to document what the organization needs.
Data Quality & Audit
Review data for quality, completeness, consistency and opportunities for improvement.
HIM & Coding Improvement
Evaluate coding, abstraction and HIM workflows and identify opportunities to improve accuracy, efficiency and data quality.
Change Management
Support teams through process and organizational change so improvements are implemented, adopted and sustained.
Education & Training
Address knowledge gaps identified during the assessment.
Staff Augmentation
Provide temporary or targeted expertise where capacity or specialist skills are contributing to a problem.
Technology & Software
Evaluate whether technology can address an identified problem and recommend appropriate solutions — without beginning with a predetermined product.
Data Governance
Help clarify ownership, accountability, standards and processes surrounding important healthcare information.
Measurement & Reporting
Establish meaningful indicators to determine whether interventions are achieving the intended results.
We define what success looks like before we start.
Expected outcomes are defined before implementation and measured afterward. Results are reported back to the organization — and where necessary, findings feed into another cycle of assessment and improvement.
Good data is what makes AI work.
Computer-assisted and autonomous coding, and AI-generated clinical documentation, depend on the same underlying data, documentation and workflows this assessment examines. Fixing that foundation now is what determines whether an AI implementation succeeds later — or simply automates the same problems.
Worth asking
When an EHR implements AI for clinical documentation, does it consider the data-collection side — or only the narrative in front of the clinician?
Start with a Data Quality Assessment
We work with your team to understand how information is created, transformed and used across the organization. We identify quality issues, investigate the underlying causes and provide a prioritized roadmap for improvement.